The subject method and system are generally directed to the virtual synchronization of timing information obtained from unsynchronized communication nodes. More specifically, the subject method and system are directed to the adaptively synchronized use of timing information provided in communications messages transmitted and received between independently clocked nodes operating in a wireless communications network.
With the widespread use of wireless communications networks, and various devices—from smart phones, electronic reading devices, and laptop computers—having readily available wi-fi capability, a wealth of very practical applications may be realized by collecting the timing information contained in network messages passed between users. The nodes of a wireless communication network which send and receive network communications comply with the network's protocol and invariably include some timing information. For example, each node typically applies a timestamp when it receives and/or when it sends a message. Such timing information is based on the node's own time reference established by its own local clock.
While the applicable communications standards may impose helpful requirements on the accuracy of the local clocks, they typically are not sufficient for many applications requiring precise timing information. Unlike more sophisticated and expensive satellite navigation systems (which are synchronized to the nanosecond level based on precise atom clocks), most computer hardware used as nodes in wireless computer networks employ far less sophisticated and much less expensive quartz crystal oscillator clocks. Conventional time synchronization techniques such as network time protocol (NTP) are not sufficiently accurate. Other known time synchronization techniques such as set forth by IEEE 1588 is not adequately implemented and tends to be expensive because they require hardware support.
As a result, it is very difficult to make concerted use of timing information obtained from different nodes. System-wide use of timestamping data collected from the various nodes of a communications network cannot be made without some corrective measures to account for the nodes' disparate frames of time reference. Complicating the problem is the nonlinear behavior exhibited by local clocks used in prevalent node network cards. For the example of the widely used wireless devices complying with the IEEE 802.11 standard typically exhibit clock drifts which very significantly enough to preclude use of a standard linear line of least squares approach to fit modeling clock behavior.
If sufficient synchronization of a communication nodes' timing information could be attained, it would find highly useful application in positioning/location finding systems. Currently known wireless location systems are generally based on three separate sources of information: angle of arrival, signal strength, and time. Angle of arrival measurements, while allowing the location of nonparticipants (not participating in the given system's location protocol), require expensive antenna arrays. Signal strength based location systems require signal strength measurements at the receiver being located, which precludes their use to locate nonparticipants.
In contrast, time-based wireless location systems are based on the simple equation:D=speed of light*t  (1)By measuring time precisely, distance between nodes may be measured. By measuring multiple distances between anchor nodes having known locations and a mobile node with unknown location, location may be determined by solving the nonlinear optimization problem defined by applicable distance equations.
Numerous time-based location systems are known; however, no location system heretofore known provides the degree of accuracy, compatibility, and economy necessary for required for productive use in existing wireless network broadcast environments. There is therefore a need for a simple yet accurate time-based location system which:
1) provides the capability to locate nonparticipating nodes;
2) may be implemented using inexpensive, off-the-shelf hardware;
3) is communication protocol agnostic; and
4) locates nodes accurately, with error less than a few meters.